
Materialized Views in Postgres: Trading Freshness for Speed
How to use materialized views to speed up expensive aggregations in Postgres without silently serving stale data to your users.
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22 articles

How to use materialized views to speed up expensive aggregations in Postgres without silently serving stale data to your users.

Soft deletes look like a simple safety net, but they silently corrupt your schema, poison your queries, and break your constraints — here's what to use instead.

Postgres has a powerful built-in full-text search engine using tsvector, tsquery, and GIN indexes — no Elasticsearch cluster required for most applications.

N+1 isn't an ORM problem — learn how to implement the DataLoader batching pattern in TypeScript to collapse redundant data fetches across any data source, including microservices.

The recurring database design mistakes that cause slow queries, painful migrations, and production incidents — with practical fixes and the reasoning behind each one.

Architect multi-tenant SaaS applications using database isolation strategies, tenant-aware middleware, resource quotas, data partitioning patterns, and security boundaries that scale from ten tenants to ten thousand without redesigning the system.

Execute schema migrations on production databases without downtime using expand-contract patterns, backward-compatible changes, blue-green data strategies, and migration safety checks that prevent data loss and application errors.

A deep dive into database connection pool configuration, covering pool sizing formulas, connection lifecycle management, health checking strategies, and diagnosing pool exhaustion under production traffic patterns.

A deep dive into database connection pooling for Node.js services, covering pool sizing, health checks, failover patterns, and the common misconfigurations that cause production outages.

Implement database schema migrations that don't require downtime using expand-contract patterns, backward-compatible changes, and phased rollouts that keep your application serving traffic throughout every deployment.

Configure and optimize database connection pools for high-throughput Node.js applications with practical examples covering pool sizing, health checks, connection lifecycle management, and common pitfalls that cause pool exhaustion.

Build CDC pipelines that stream database changes to downstream systems in real time, covering log-based capture with Debezium, event formatting, schema evolution handling, and exactly-once delivery guarantees.

Compare offset, cursor, and keyset pagination strategies with practical implementations showing performance characteristics, trade-offs, and when each approach fits your API design.

A practical breakdown of read uncommitted, read committed, repeatable read, and serializable isolation levels — with real examples of the anomalies each one prevents and the performance trade-offs involved.

A practical guide to database sharding — covering partitioning strategies, shard key selection, cross-shard queries, and the operational complexity that comes with distributing data.

Explore Redis data structures beyond simple strings — sorted sets for leaderboards, streams for event logs, HyperLogLog for cardinality, and bitmaps for feature flags.

How to configure and monitor database connection pools — covering pool sizing, leak detection, failover handling, and common misconfiguration pitfalls.

Patterns for integration tests that are reliable, fast, and catch real bugs — covering database setup, API testing, and avoiding flaky test syndrome.

Practical techniques for identifying and fixing slow SQL queries using EXPLAIN plans, indexing strategies, and query restructuring patterns.

Opening a new database connection per request is a silent performance killer — connection pools solve this with a managed set of reusable connections.

Schema changes are the most dangerous deploys — here are the patterns for zero-downtime migrations, rollback safety, and avoiding data loss.

Indexes can make or break your application's performance — here's how they work under the hood and when to use each type.